The specification relates to managing user activities. More specifically, the specification relates to identifying a first event, identifying overlapping activities between the first event and a second event and updating the first event to include information from the second event.
An automated understanding of a person's behavior—what they are doing, their state of mind, and the overall context they are in—is a very difficult challenge. On the input side, enormous amounts of user data are available across different platforms including applications on the user's mobile device and personal desktop. For example, the user may use applications stored on the mobile device to read books, listen to music, view web pages, play games, etc. There are also many on-device sensors (e.g., accelerometers), environmental sensors (e.g., a motion sensor), as well as other signals, like whether a phone is currently plugged into a power outlet or not. These and other signals can also be used to help understand a user's behavior. Due to the large volume of data associated with the user, it can be difficult to get an overall understanding of the user's activities.
On the output side, human behavior is composed of many layers and complexities. There are individual activities that a user might be doing: playing a game on their phone, running, riding a train, or checking email. At a higher level the person might be at home, at work or on vacation. A person might be transitioning from place A to place B as a daily commute, as a business trip or as a permanent relocation.